mirror of
https://github.com/hwchase17/langchain
synced 2024-11-10 01:10:59 +00:00
110 lines
3.2 KiB
Python
110 lines
3.2 KiB
Python
from __future__ import annotations
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from typing import Any, Callable, Dict, Optional
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from langchain_core.output_parsers import BaseOutputParser
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class GuardrailsOutputParser(BaseOutputParser):
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"""Parse the output of an LLM call using Guardrails."""
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guard: Any
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"""The Guardrails object."""
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api: Optional[Callable]
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"""The LLM API passed to Guardrails during parsing. An example is `openai.completions.create`.""" # noqa: E501
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args: Any
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"""Positional arguments to pass to the above LLM API callable."""
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kwargs: Any
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"""Keyword arguments to pass to the above LLM API callable."""
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@property
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def _type(self) -> str:
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return "guardrails"
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@classmethod
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def from_rail(
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cls,
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rail_file: str,
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num_reasks: int = 1,
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api: Optional[Callable] = None,
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*args: Any,
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**kwargs: Any,
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) -> GuardrailsOutputParser:
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"""Create a GuardrailsOutputParser from a rail file.
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Args:
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rail_file: a rail file.
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num_reasks: number of times to re-ask the question.
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api: the API to use for the Guardrails object.
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*args: The arguments to pass to the API
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**kwargs: The keyword arguments to pass to the API.
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Returns:
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GuardrailsOutputParser
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"""
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try:
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from guardrails import Guard
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except ImportError:
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raise ImportError(
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"guardrails-ai package not installed. "
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"Install it by running `pip install guardrails-ai`."
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)
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return cls(
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guard=Guard.from_rail(rail_file, num_reasks=num_reasks),
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api=api,
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args=args,
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kwargs=kwargs,
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)
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@classmethod
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def from_rail_string(
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cls,
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rail_str: str,
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num_reasks: int = 1,
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api: Optional[Callable] = None,
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*args: Any,
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**kwargs: Any,
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) -> GuardrailsOutputParser:
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try:
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from guardrails import Guard
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except ImportError:
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raise ImportError(
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"guardrails-ai package not installed. "
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"Install it by running `pip install guardrails-ai`."
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)
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return cls(
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guard=Guard.from_rail_string(rail_str, num_reasks=num_reasks),
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api=api,
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args=args,
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kwargs=kwargs,
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)
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@classmethod
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def from_pydantic(
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cls,
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output_class: Any,
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num_reasks: int = 1,
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api: Optional[Callable] = None,
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*args: Any,
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**kwargs: Any,
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) -> GuardrailsOutputParser:
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try:
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from guardrails import Guard
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except ImportError:
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raise ImportError(
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"guardrails-ai package not installed. "
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"Install it by running `pip install guardrails-ai`."
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)
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return cls(
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guard=Guard.from_pydantic(output_class, "", num_reasks=num_reasks),
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api=api,
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args=args,
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kwargs=kwargs,
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)
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def get_format_instructions(self) -> str:
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return self.guard.raw_prompt.format_instructions
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def parse(self, text: str) -> Dict:
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return self.guard.parse(text, llm_api=self.api, *self.args, **self.kwargs)
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